High Hydrogen Permeance Silica Membranes Prepared by a Chemical Vapor Deposition Method
Bibliographic record
Abstract
H2 permselective silica hybrid membranes were successfully prepared by using a counter diffusion chemical vapor deposition (CVD) method. Hexyltrimethoxysilane (HTMOS), phenyltrimethoxysilane (PhTMOS) or diphenyldimethoxysilane (DPhDMOS) were used as silica precursors. The oxidants were O3 or O2. These reactants were provided at the opposite side of the γ-alumina substrates, and the deposition occurred in the pores of the substrates. The HTMOS/O3 derived membrane deposited at 450°C showed the highest H2 permselectivity. The H2 permeace was 2.1×10-6 mol m-2 s-1 Pa-1 with the H2/SF6 permeance ratio of 5.9×106. H2 permeances through the HTMOS derived membranes increased with increasing the deposition temperatures. While the H2 permeance through the PhTMOS and DPhDMOS derived membranes decreased with increasing the deposition temperatures. The PhTMOS derived membrane prepared at 150°C showed the H2 permeance of 1.7×10-6 mol m-2 s-1 Pa-1 with the H2/SF6 permeance ratio of 13. The PhTMOS membrane prepared at 320°C showed the highest H2/SF6 permeance ratio of 1.8×104among the PhTMOS derived membranes. However, the H2/SF6 permeance ratio through the DPhDMOS membranes showed the different trend. Higher H2/SF6 permeance ratio was found through the DPhDMOS derived membranes deposited at 180°C and 360°C. The maximum H2/SF6 permeance ratio was 4.2×104 through the DPhDMOS membrane deposited at 180°C. The decomposition properties of organic groups on silica surface are investigated by using hydrolysis powders derived from the each silica precursor. The HTMOS powders showed O3 stability after the high temperature treatment. Thus, high H2 permselective membranes were prepared by the HTMOS at 450 °C.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".